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This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The purpose of this study is to examine the moderating effect of two types of external funds in terms of loan and government subsidy on the relationship between R&D investment and firms' innovation performance in emerging markets, as well as the contingent role of firm leader's international experience associated with the effects of loan and government subsidy.

The authors tested the hypotheses using a longitudinal dataset of 716 high-tech firms of Zhongguancun Science Park (ZSP) in China during 2008–2014, covering detailed information on the operations, financial situation and R&D activities, patents, etc. The authors finally identified an unbalanced panel of 2,430 firm-year observations. Considering the dependent variable is the countable data and non-negative values, the negative binomial regression with fixed effects was adopted to test the hypotheses.

The results show that the more loans or government subsidies the firm receives, the weaker the positive effect of R&D investment on firms' innovation performance in emerging markets. Furthermore, the findings reveal that firm leaders' international experience can mitigate the negative moderating effect of government subsidies, but strengthen the negative moderating effect of loans.

The study provides new insights into how loans and government subsidies as external funds influence the effectiveness of R&D in enhancing innovation performance, and the findings highlight the fact that more external funds can reduce firm R&D efficiency. Moreover, the authors also enrich the resource orchestration theory by revealing the critical role of firm leaders' international experience in the decision-making of resource configuration to mitigate the inefficiency of high subsidies in emerging markets.

The purpose of this study is to investigate the effect of the COVID-19 pandemic on key performance metrics of accommodation properties by elaborating on the roles of business models (i.e. franchised, chain-managed and independent hotels, and the sharing economy) and state-level restrictions in the US.

The pandemic is considered a variable interference against the average daily rate, occupancy and revenue per available room, which permits the examination of the before and after effects of the pandemic. The panel data model is used to examine the effect of the recent pandemic on the accommodation sector in the USA.

The results showed that chain-managed hotels were the most adversely impacted by the COVID-19 pandemic, while independent hotels were the least adversely impacted. Interestingly, and consistent with emerging consumer needs suggested by spatial distance theory, the pandemic does not have significant negative effects on Airbnb. The adverse impact of the pandemic on hotels was exacerbated in more restrictive states, while Airbnb remained immune to regulatory differences.

This study addresses the dearth of research on the types, roles and efficacy of business models in the accommodation industry and makes important theoretical contributions to the study of business model resilience in the accommodation industry, leveraging the resource-based theory of the firm and spatial distance theory.

The findings of this study make a significant contribution to the extant literature on the resilience of business models in the accommodation industry and have important implications for hotels, Airbnb owners, accommodation brands and destination and health policymakers. They demonstrate that a lower level of corporate control and greater flexibility in brand and operational standards allow for a more effective response to business disruptions such as a global pandemic.

Urban mobility has substantially evolved in several western countries, shifting from interest in road expansion strategies to cater motorized movement to the emphasis on sustainable mobility. This is, however, not the case in several developing countries that still try to accommodate vehicular flows in inner historic cities. This paper aims at providing an assessment framework that helps in evaluating the effect of streetscape development on the walking and cycling environment in historic contexts.

This research follows a two-phase methodology. Phase 1 is the investigation of the literature review including the streetscape design, Sustainable Development Goals (SDGs) and indicators for the assessment of walking and cycling environment. This phase results in developing a set of indicators for the assessment. Phase 2 is the case study including, methods, steps and results of the assessment based on the output of Phase 1. This phase concludes with a discussion on the challenges and recommendations for the enhancement.

The streetscape development in Afrang was insufficient and negatively affected the walking and cycling environment. It was motorized-oriented, instead of enhancing green mobility. The interventions led to more crowds, safety risks and less pleasant experience. Moreover, the car users' experience was enhanced initially; however, the traffic situation did not persist. A sustainable urban mobility approach is necessary to be implemented with consideration to the global level and the relation to SDGs.

There is a gap in tackling the research problem both within the context of Port Said in particular and Egyptian context in general. Local authorities need a clear structured methodology to follow in the development of the streetscape. The assessment indicators gathered can be the basis for evaluating future plans.

This study aims to identify the determinants that influence citizen’s behavioural intention and continuous usage intention of smart mobility services in Indian smart cities with the help of an extended technology acceptance model.

This study uses a quantitative methodology to analyse the data collected from 509 residents of smart cities in India. The study used the partial least squares structural equation modelling approach to test the proposed hypotheses.

The study highlights the importance of perceived usefulness and ease of use in influencing citizens’ attitudes and intentions towards smart mobility services. Positive attitudes significantly impact behavioural intentions, which, in turn, link to continuous usage intentions.

This study contributes to the existing body of knowledge on smart cities and technology adoption, specifically in the area of smart mobility. The study’s findings will help service providers and policymakers to develop more robust strategies for the future.

Drawing on the challenge–hindrance stressor framework and the “too-much-of-a-good-thing” principle, this study examined the curvilinear effects of two emic social challenge stressors (guanxi beliefs and participative decision-making (PDM)) and the moderating effect of an etic social hindrance stressor (perceived organizational politics) on Hong Kong and United States nurses’ job satisfaction.

A quantitative survey method was implemented, with the data provided by 355 Hong Kong nurses and 116 United States nurses. Structural equation modeling was used to examine the degree of measurement equivalence across Hong Kong and US nurses. The proposed model and the research questions were tested using nonlinear structural equation modeling analyses.

The results show that while guanxi beliefs only showed an inverted U-shaped relation on Hong Kong nurses’ job satisfaction, PDM had an inverted U-shaped relation with both Hong Kong and United States nurses’ job satisfaction. The authors also found that Hong Kong nurses experienced the highest job satisfaction when their guanxi beliefs and perceived organization politics were both high.

The results add to the comprehension of the nuances of the often-held assumption of linearity in organizational sciences and support the speculation of social stressors-outcomes linkages.

Managers need to recognize that while the nurturing and development of effective relationships with employees via social interaction are important, managers also need to be aware that too much guanxi and PDM may lead employees to feel overwhelmed with expectations of reciprocity and reconciliation to such an extent that they suffer adverse outcomes and become dissatisfied with their jobs.

First, the authors found that influences of guanxi beliefs and PDM are not purely linear and that previous research may have neglected the curvilinear nature of their influences on job satisfaction. Second, the authors echo researchers’ call to consider an organization’s political context to fully understand employees’ attitudes and reactions toward social interactions at work. Third, the authors examine boundary conditions of curvilinear relationships to understand the delicate dynamics.

Employees facing challenges in their careers – i.e. female, migrant, elderly and lower-educated employees – might expect job searches to have a low likelihood of success and might therefore more often stay in unsatisfactory positions. The goal of this study is to discover inequalities in job mobility for these employees.

We rely on a large sample of Dutch public sector employees (N = 30,709) and study whether employees with challenges in their careers are hampered in translating job dissatisfaction into job searches. Additionally, we assess whether this is due to their perceptions of labor market alternatives.

Findings show that non-Western migrant, elderly and lower-educated employees are less likely to act on job dissatisfaction than their advantaged counterparts, whereas women are more likely than men to do so. Additionally, we find that although they perceive labor market opportunities as limited, this does not affect their propensity to search for different jobs.

This paper is novel in discovering inequalities in job mobility by analyzing whether employees facing challenges in their careers are less likely to act on job dissatisfaction and therefore more likely to remain in unsatisfactory positions.

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.

A trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.

Six volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.

The AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

Cambodian and Laotian students (CLS) are among the largest groups of international students in intra-ASEAN student mobility as well as in Vietnamese higher education institutions (HEIs). However, little has been researched on the factors influencing CLS’s decision to choose Vietnam as destination country. The purpose of this study is to investigate why CLS decide to go overseas and choose Vietnam as their host country among other opportunities as well as their perceptions of the decision.

Using qualitative methods and employing purposive sampling, data were collected by semi-structured interviews from CLS studying in a HEI in the Mekong Delta of Vietnam. The data were analysed against the push–pull framework to understand factors influencing the participants’ decision.

The findings show that CLS in the study were “pushed” by the perceived higher value of a foreign qualification and family encouragements. In terms of pull factors, they were attracted to choose Vietnam as the host country most observably due to scholarship opportunities. However other pull factors were also significant, especially the lack of certain skills in home countries and its congruence with Vietnam’s competitive strength in offering courses for those skills. In retrospect, the participants expressed a sense of optimism, though there was also certain reservation.

The small sample restrict the generalisability of the findings.

As an exploratory study, the findings can lay the ground for largerscale studies investigating CLS mobility in Vietnam and be employed for inbound student mobility policymaking reference for HEIs in Vietnam as well as in other developing countries.

This study investigates why Cambodian and Laotian international students decide to go to Vietnam, a developing country in the lesser-known part of international student mobility landscape. This is a topic that remains under-researched in the Asia-bound student mobility literature. Insights from the study can not only contribute to the scholarly gap but also offer implications for HEIs in Vietnam and other Asian countries.